Pedestrian Injury Severity in Automobile Crashes

Pedestrian-vehicle crashes can result in serious injury to pedestrians, who are exposed to danger when in close proximity to moving vehicles. Furthermore, these injuries can be considerably serious and even lead to death in a manner that varies depending on the pedestrian’s age. This is because the pedestrian’s physical characteristics and behaviors, particularly in relation to roads with moving vehicles, differ depending on the pedestrian’s age. This study examines the determinants of pedestrian injury severity by pedestrian age using binary logistic regression. Factors in the built environment, such as road characteristics and land use of the places where pedestrian crashes occurred, were considered, as were the accident characteristics of the pedestrians and drivers. The analysis determined that the accident characteristics of drivers and pedestrians are more influential in pedestrian-vehicle crashes than the factors of the built environmental characteristics. However, there are substantial differences in injury severity relative to the pedestrian’s age. Young pedestrians (aged under 20 years old) are more likely to suffer serious injury in school zones; however, no association between silver zones and injury severity is found for elderly pedestrians. For people in the age range of 20–39 years old, the severity of pedestrian injuries is lower in areas with more crosswalks and speed cameras. People in the age range of 40–64 years old are more likely to be injured in areas with more neighborhood streets and industrial land use. Elderly pedestrians are likely to suffer fatal injuries in areas with more traffic signals. This study finds that there are differences in the factors of pedestrian injury severity according to the age of pedestrians. Therefore, it is suggested that concrete and efficient policies related to pedestrian age are required to improve pedestrian safety and reduce pedestrian-vehicle crashes.

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Examining pedestrian-injury severity using alternative disaggregate models

Research in Transportation Economics ◽

10.1016/j.retrec.2012.12.002 ◽

2013 ◽

Vol 43 (1) ◽

pp. 123-136 ◽

Cited By ~ 29

Author(s):

Kibrom A. Abay

Keyword(s):

Injury Severity ◽

Pedestrian Injury ◽

Disaggregate Models

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Inconsistencies of Ordered and Unordered Probability Models for Pedestrian Injury Severity

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2264-13 ◽

2011 ◽

Vol 2264 (1) ◽

pp. 110-118 ◽

Cited By ~ 10

Author(s):

Valerian Kwigizile ◽

Thobias Sando ◽

Deo Chimba

Keyword(s):

Injury Severity ◽

Probability Models ◽

Pedestrian Injury

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Investigating factors influencing pedestrian injury severity at intersections

Traffic Injury Prevention ◽

10.1080/15389588.2017.1354371 ◽

2017 ◽

Vol 19 (2) ◽

pp. 159-164 ◽

Cited By ~ 4

Author(s):

Zhuanglin Ma ◽

Xi Lu ◽

Steven I-Jy Chien ◽

Dawei Hu

Keyword(s):

Injury Severity ◽

Factors Influencing ◽

Pedestrian Injury

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Pedestrian Injury Severities in Pedestrian-Vehicle Crashes and the Partial Proportional Odds Logit Model: Accounting for Age Difference

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198119842828 ◽

2019 ◽

Vol 2673 (5) ◽

pp. 731-746 ◽

Cited By ~ 7

Author(s):

Yang Li ◽

Wei (David) Fan

Keyword(s):

Logit Model ◽

Injury Severity ◽

Parameter Estimates ◽

Age Difference ◽

Age Group ◽

Vehicle Crashes ◽

Ordered Logit ◽

Proportional Odds ◽

Pedestrian Injury ◽

Injury Severities

This study investigates factors that significantly contribute to the severity of pedestrian injuries resulting from pedestrian-vehicle crashes. Multinomial logit (MNL) models, mixed logit (ML) models, and ordered logit/probit models have been widely used in modeling crash injury severity, including pedestrian injury severity in pedestrian-vehicle crashes. However, both MNL and ML models treat injury severity levels as non-ordered, ignoring the inherent hierarchical nature of crash injury severities, and the data used in ordered logit models need to be strictly subjected to the proportional odds (PO) assumption. In this study, a partial proportional odds (PPO) logit model approach is employed to explore the issues of pedestrian safety associated with each age group: young (aged under 24), middle-aged (aged 25–55), and older pedestrians (aged over 55). Data used in this study are police-reported pedestrian crash data collected from 2007 to 2014 in North Carolina. A variety of motorist, pedestrian, environmental, and roadway characteristics are inspected. Results from likelihood ratio tests statistically show the better performance of developing separate injury severity models for each age group compared with estimating a single model utilizing all data. Relevant parameter estimates and associated marginal effects are used to interpret the results, followed by recommendations made in the concluding section.

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